windows WSL2 ubuntu 安裝 deepo 深度學(xué)習(xí)環(huán)境

第二步 docker以及deepo

1. windows部分

CUDA on WSL

NVIDIA Drivers for CUDA on WSL, including DirectML Support

安裝windows 部分的驅(qū)動

2. ubuntu部分-docker

若出錯請逐行復(fù)制

• nvidian docker

sudo apt-get update

curl <https://get.docker.com> | sh

distribution=$(. /etc/os-release;echo $ID$VERSION_ID)

curl -s -L <https://nvidia.github.io/nvidia-docker/gpgkey> | sudo apt-key add -

curl -s -L <https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list> | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

curl -s -L <https://nvidia.github.io/libnvidia-container/experimental/$distribution/libnvidia-container-experimental.list> | sudo tee /etc/apt/sources.list.d/libnvidia-container-experimental.list

sudo apt-get install -y nvidia-docker2

• docker

sudo apt-get remove docker docker-engine docker.io containerd runc
sudo apt-get update

sudo apt-get install \\
    apt-transport-https \\
    ca-certificates \\
    curl \\
    gnupg-agent \\
    software-properties-common
curl -fsSL <https://download.docker.com/linux/ubuntu/gpg> | sudo apt-key add -

sudo apt-key fingerprint 0EBFCD88

sudo add-apt-repository \\
   "deb [arch=amd64] <https://download.docker.com/linux/ubuntu> \\
  $(lsb_release -cs) \\
  stable"

sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io
sudo docker run hello-world

• 啟動docker

serviece docker start

若報錯：docker: unrecognized service

查看 /var/lib/ 目錄下是否有 docker 目錄，我的是有 docker-desktop，有些是 docker，自己看。 執(zhí)行命令：sudo rm -rf /var/lib/docker-desktop/

3. ubuntu 部分 cuda toolkits

官網(wǎng)下載對應(yīng)支持的cuda tookits，離線下載后再安裝比較快

CUDA Toolkit 11.2 Downloads

例如： ubuntu 20.04

wget <https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin>
sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget <https://developer.download.nvidia.com/compute/cuda/11.2.0/local_installers/cuda-repo-ubuntu2004-11-2-local_11.2.0-460.27.04-1_amd64.deb>
sudo dpkg -i cuda-repo-ubuntu2004-11-2-local_11.2.0-460.27.04-1_amd64.deb
sudo apt-key add /var/cuda-repo-ubuntu2004-11-2-local/7fa2af80.pub
sudo apt-get update
sudo apt-get -y install cuda

大文件在瀏覽器中下載 （命令第三行的網(wǎng)址取出）

https://developer.download.nvidia.com/compute/cuda/11.2.0/local_installers/cuda-repo-ubuntu2004-11-2-local_11.2.0-460.27.04-1_amd64.deb

進入下載目錄，運行安裝命令

cd /mnt/c/User/用戶名/Downloads

sudo dpkg -i cuda-repo-ubuntu2004-11-2-local_11.2.0-460.27.04-1_amd64.deb

4 deepo 鏡像

方法1 在線拉?。?選一個好網(wǎng)（長城寬帶，部分校園網(wǎng)不行，可以用熱點）

ufoym/deepo

docker pull ufoym/deepo

或者

docker pull [registry.docker-cn.com/ufoym/deepo](<http://registry.docker-cn.com/ufoym/deepo>)

方法2： 離線版本：網(wǎng)盤分享

鏈接：https://pan.baidu.com/s/1g4alJbefNBcPaIb0lPyAIw 提取碼：1111 復(fù)制這段內(nèi)容后打開百度網(wǎng)盤手機App，操作更方便哦--來自百度網(wǎng)盤超級會員V6的分享

cd /mnt c（例如保存至在c的根目錄下）

進入目錄后docker load < deepo.tar等待一段時間即可

5 運行

service docker start 
docker run --gpus all -it -p 8888:8888 ufoym/deepo bash 
jupyter notebook --allow-root --ip 0.0.0.0

在Windows瀏覽器中輸入 localhost:8888/?xxxxxxxxxxxx (xxxx為命令窗口中的token)

終端

jupyter torch 測試